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PubMed2026

Uncovering hub genes and key pathways responsive to drought stress in rice via meta-analysis of transcriptomic data.

Drought stress presents a formidable threat to global rice cultivation, triggering complex molecular responses that impact plant growth and productivity. To decipher the underlying gene expression dynamics, we performed a comprehensive meta-analysis of transcriptomic datasets derived from drought-tolerant rice genotypes. Via microarray data from three independent studies, we identified a set of consistently expressed differentially expressed genes (DEGs) under drought conditions. Integration of functional annotation tools, including GO and KEGG pathway enrichment, revealed key biological processes and signaling cascades involved in stress mitigation, such as ABA signaling, protein folding, and photosynthesis suppression. Protein-protein interaction (PPI) network construction, followed by hub gene identification via maximal clique centrality (MCC), highlighted pivotal regulators including LEA proteins, dehydrins, HSP70, and several transcription factors. Machine learning approaches further prioritize potential biomarkers, with Random Forest models achieving high classification accuracy and pinpointing key predictive genes. Chromosomal localization analysis provided spatial insights into the distribution of these hub genes, whose expression patterns were further compared against qRT-PCR data from previously published studies. This integrative approach identifies candidate genomic markers and mechanistic insights that may support future breeding strategies for drought-tolerant rice, pending experimental validation.

Cytoscape↗

PubMed2025

Targeting RAD52 overcomes PARP inhibitor resistance in preclinical Brca2-deficient ovarian cancer model.

BRCA-mutated ovarian cancer commonly develops resistance to poly (ADP-ribose) polymerase (PARP) inhibitors. Here, we investigated the DNA repair protein RAD52 as a potential target to overcome resistance. In analysis of The Cancer Genome Atlas datasets and immunohistochemistry of tissue microarrays, elevated RAD52 expression correlated with poor overall survival in patients with high-grade serous ovarian cancers. We tested two PARP inhibitor-resistant Brca2-deficient mouse ovarian cancer models, ID8-OR and HGS2-OR. HGS2-OR cells had higher RAD52 expression than parental lines. Rad52 knockout or knockdown restored PARP inhibitor sensitivity in both models. In syngeneic mice, ID8-OR cells in which Rad52 was knocked out yielded lower tumor burden and longer overall survival than control cells. Rad52 depletion impaired single-strand annealing and homologous recombination and led to accumulation of DNA double-strand breaks after PARP inhibitor treatment. RNA sequencing demonstrated that PARP inhibitor treatment induced Polq expression in Brca2- and Rad52-deficient cells, suggesting a switch to microhomology-mediated end joining. Finally, the RAD52 inhibitor D-I03 synergized with a PARP inhibitor to reduce cell viability and tumor burden and prolong survival. Collectively, our findings establish RAD52 as a promising therapeutic target to overcome PARP inhibitor resistance in BRCA2-mutated ovarian cancer and offer mechanistic insights to inform future clinical strategies.

Journal Article↗

PubMed2026

Human periodontal ligament stem cells promote oral ulcer healing in rats through modulation of TGF-β1/smad signaling.

BACKGROUND: Oral ulcers (OU) often present with prolonged healing, recurrent episodes, and scar formation, posing challenges for clinical management. Human periodontal ligament stem cells (hPDLSCs) have shown potential in oral tissue repair, but further research is needed to clarify their mechanism of action in OU healing. This study aims to elucidate the molecular mechanisms by which hPDLSCs promote oral ulcer healing. METHOD: To identify key regulatory genes, the OU-associated microarray dataset GSE37265 was integrated with hPDLSC genomic data for differential expression analysis. Subsequently, Weighted Gene Co-expression Network Analysis (WGCNA) was used to identify functional modules associated with OU healing. In vivo, hPDLSCs were locally administered into a rat ulcer model, and therapeutic efficacy was assessed by ulcer closure rates and histological evaluation (HE and Masson's trichrome staining). Furthermore, RNA-sequencing (RNA-seq) was performed on oral mucosal tissues to delineate the underlying molecular landscape and critical signaling pathways. The involvement of the TGF-β signaling pathway was confirmed by real-time quantitative PCR (RT-qPCR) and Western blotting (WB) analyses. RESULTS: Bioinformatics analysis identified 92 key genes in hPDLSCs-mediated treatment of OU, highlighting the central role of the TGF-β1/Smad pathway. As shown by the animal studies, hPDLSCs therapy increased the healing rate to 97% by day 8 (vs. 70% in the model). Furthermore, the therapy significantly reduced inflammatory cell infiltration and abnormal collagen deposition while promoting regular collagen arrangement. Transcriptomic and molecular experiments further showed that hPDLSCs simultaneously inhibit TGF-β1/Smad and extracellular signal-regulated kinase (ERK) signaling pathways, thereby alleviating inflammatory responses and suppressing mucosal fibrosis. CONCLUSION: In this study, we reveal a novel role for hPDLSCs in promoting oral ulcer healing. The findings indicate that hPDLSCs suppress inflammation and fibrosis via the TGF-β1/Smad pathway, offering a promising therapeutic strategy for OU and other fibrotic conditions.

TGF-β1↗

PubMed2026

Profibrogenic Gremlin-1 expression in prostate cancer and the clinicopathologic association.

BACKGROUND: Gremlin-1 (GREM1) is a profibrogenic molecule involved in TGF-β signaling. Recent studies have implicated GREM1 in androgen receptor (AR)-independent signaling and castration resistance in advanced prostate cancer. However, its compartment expression patterns and clinicopathologic significance in primary prostate cancer remain unclear. METHODS: GREM1 mRNA expression and clinicopathologic associations were analyzed in the Cancer Genome Atlas (TCGA) prostate adenocarcinoma (TCGA-PRAD), the Memorial Sloan Kettering Cancer Center (MSKCC), and the German Cancer Research Center (DKFZ) primary prostate cancer cohorts. Correlations between GREM1 and genes related to TGF-β signaling, extracellular matrix organization, fibroblast activation, and AR signaling were evaluated by Spearman analysis. GREM1 protein expression was examined by immunohistochemistry in commercial human prostate cancer tissue microarrays (TMAs) using compartment-specific QuPath-based H-scores. RESULTS: GREM1 expression was relatively elevated in prostate and bladder cancers. Across the three prostate cancer cohorts, higher GREM1 expression was associated with adverse pathologic features and was most consistently correlated with FAP. Inverse correlations were observed with selected AR-related genes, whereas no significant correlation was found with AR itself. Higher GREM1 expression was associated with shorter disease-free survival only in MSKCC but was not an independent prognostic factor after clinicopathologic adjustment. Quantitative immunohistochemistry in 43 patients showed higher epithelial than stromal GREM1 H-scores (median, 3.10 vs 1.41; P < 0.0001), with heterogeneous staining in both compartments. Neither epithelial nor stromal H-scores were associated with Gleason score or pathologic T stage. CONCLUSIONS: GREM1 mRNA expression in primary prostate cancer was associated with adverse clinicopathologic features, and a fibroblast-associated transcriptional context but did not demonstrate independent prognostic value. At the protein-level, GREM1 expression was heterogeneous in both epithelial and stromal compartments, with higher epithelial H-scores on average. These findings support further investigation of the biological significance of GREM1 expression in primary prostate cancer.

TCGA↗

PubMed2026

Profiling Dectin-2-Positive Tumor-Associated Macrophages Across Human Cancers by Immunohistochemistry.

PURPOSE: To characterize the prevalence and distribution of Dectin-2-positive macrophages across human tumors and develop a research immunohistochemistry (IHC) assay to assess Dectin-2 in cancer tissues. MATERIALS AND METHODS: C-type lectin domain family 6 member A (CLEC6A), the gene encoding Dectin-2, was evaluated across 38 tumor types using The Cancer Genome Atlas. A fit-for-purpose Dectin-2 IHC assay was developed using a monoclonal antibody selected from screening 11 anti-Dectin-2 antibodies. Assay performance was supported by Dectin-2-expressing and parental cell line controls, macrophage-associated staining patterns, and comparison with an orthogonal CLEC6A in situ hybridization method using RNAscope. Dectin-2 expression was assessed in tissue microarrays (n = 553 samples) across 6 cancer types and whole tissue sections (n = 137) across 7 cancer types. RESULTS: The Cancer Genome Atlas analysis identified enriched CLEC6A expression in several tumor types, including non-small cell lung cancer (NSCLC), triple-negative breast cancer (TNBC), and subsets of head and neck cancer (HNC) and colorectal cancer (CRC). By IHC, Dectin-2-positive macrophages were detected across tumor types, with notable heterogeneity within and across cancer types. In tissue microarrays, NSCLC showed the highest frequency of Dectin-2-positive macrophage infiltration, with 38% of cases with staining ≥1% of tumor area. Whole tissue section analysis confirmed and expanded these findings, with ≥50% of NSCLC, melanoma, HNC, TNBC, and CRC samples showing Dectin-2-positive macrophages in ≥1% tumor area. CONCLUSIONS: Dectin-2 expression was observed in subsets of tumor-associated macrophages across multiple human cancers, with relatively enriched expression in NSCLC, melanoma, HNC, TNBC, and CRC. To our knowledge, this study represents the first broad protein-level characterization of Dectin-2 across multiple human tumor types, identifies cancers with relatively enriched Dectin-2-positive macrophage infiltration, and provides a foundation for future translational studies of Dectin-2-targeted therapies.

Humans↗

PubMed2026

Microrna Expression in Aurelia aurita Metamorphosis.

INTRODUCTION: In animal taxa and jellyfish, the same genome encodes for the different phenotypes that characterize life stages that follow each other during ontogeny. This situation underscores the existence of profound regulation of genomic information at the epigenetic level. MicroRNAs are fundamental epigenetic regulators. The aim of this study is to evaluate the role of microRNA regulation during jellyfish metamorphosis and to explore the existence of evolutionarily conserved microRNAs. METHODS: Specimens belonging to the 4-metamorphosis stages of A. aurita (polyps, ephyra, young, and adult jellyfish) were bred and collected. The expression of 2,549 miRNAs for each stage was tested using microarray technology. The comparison of microRNA expression for each phase was performed using line plot analysis and Principal Component Analysis of variance (PCA), while the identification of microRNA clusters was performed via volcano plot analysis. RESULTS: A remarkable number of A. aurita miRNAs specifically hybridize with a human miRNA library. Each metamorphosis stage is characterized by a different level of expression of miRNAs: 1) Polyp vs. Ephyra stage: 128 upregulated, 2 downregulated; 2) Ephyra vs. Young stage: 2 upregulated, 135 downregulated; 3) Young vs. Adult stage: 69 upregulated, 6 downregulated. Specific functions inferred from known activities of corresponding miRNAs in higher animals (PubMed database) appear to be coherent with the correlated experimental model. DISCUSSION: Present results reveal that microRNAs with human homologs undergo specific expression changes throughout Aurelia aurita metamorphosis. This observation reinforces the hypothesis of a shared evolutionary origin of certain miRNA families between Cnidaria and Bilateria. The dynamic and stage-specific regulation pattern observed suggests that miRNAs play a key role in orchestrating the complex transitions involved in jellyfish development. These findings point to a broader conservation of epigenetic mechanisms, such as miRNA-mediated gene silencing, which may have emerged early in metazoan evolution and contributed to the regulation of cell differentiation and phenotype modulation. CONCLUSION: The present study highlights the importance of Aurelia aurita as a model for investigating miRNA-driven epigenetic regulation in non-bilaterian animals. The identification of human-homologous miRNAs provides novel insights into the evolutionary stability of the epigenetic machinery and suggests conserved regulatory functions across distant taxa. Although limited by the use of a human-based microarray platform, the data presented here lay a solid foundation for future studies employing sequencing and functional assays to further explore the role of miRNAs in cnidarian development and evolution.

Animals↗

PubMed2026

slideimp: efficient imputation of DNA methylation data.

SUMMARY: We developed slideimp, an R package that extends and optimizes K-nearest neighbor (K-NN) and Principal Component Analysis (PCA) imputation with grouped and sliding-window modes for accurate and efficient imputation of microarray and whole-genome DNA methylation (DNAm) data, respectively. Under a realistic scenario, slideimp achieved ≈12-28× faster runtime and ≈3-6× peak memory usage reduction for DNAm microarray imputation (GSE286313, EPICv2, N = 72) and achieved high imputation accuracy in a whole-genome DNAm dataset (N = 41). AVAILABILITY AND IMPLEMENTATION: The code used in this study is available at https://github.com/hhp94/slideimp_paper. The R package slideimp is available on CRAN (DOI: 10.32614/CRAN.package.slideimp). Version 1.0.0 of slideimp, which was used in this study, is archived on Zenodo (DOI: 10.5281/zenodo.20029382).

DNA Methylation↗

PubMed2026

KLF5 promotes proliferation, migration, and autophagy-/EMT‑associated molecular changes in lens epithelial cells via transcriptional activation of THBS1 in traumatic cataract.

PURPOSE: Traumatic cataract is a common blinding eye disease after ocular trauma, and its pathogenesis is closely related to lens epithelial cell dysfunction, while the definite molecular regulatory mechanism between upstream transcription factor and downstream target gene remains poorly clarified. This study aimed to clarify the role and molecular mechanism of the krüppel-like factor 5 (KLF5)/ thrombosponin 1 (THBS1) axis in regulating proliferation, migration, epithelial-mesenchymal transition and autophagy of lens epithelial cells in traumatic cataract, and to explore its potential clinical therapeutic value. METHODS: The GSE295383 dataset in the gene expression omnibus (GEO) database was downloaded, and the differentially expressed genes (DEGs) were screened by linear models for microarray data (limma) package of R language. Combined with Weighted gene co-expression network analysis (WGCNA), the gene co-expression network was constructed and the key modules were screened. Gene ontology (GO), kyoto encyclopedia of genes and genomes (KEGG) and gene set enrichment analysis (GSEA) combined with human transcription factor target (hTFtarget) and JASPAR databases were used to predict the upstream transcription factors of THBS1. Subsequently, SRA01/04 cells were induced with transforming growth factor-beta 2 (TGF-β2) to construct a cataract cell model. RESULTS: THBS1 and KLF5 were highly expressed in LECs exposed to TGF-β2. KLF5 could activate THBS1 transcription by binding to THBS1 promoter - 174 to -165 sites. Knockdown of THBS1 inhibited TGF-β2-induced viability, proliferation, migration, and altered the expression of epithelial-mesenchymal transition (EMT)- and autophagy-related markers in LECs. Knockdown of KLF5 downregulated THBS1 expression and produced a similar inhibitory effect, while overexpression of THBS1 reversed the effect of KLF5 knockdown. CONCLUSIONS: This study demonstrated that KLF5 promoted the proliferation, migration, and EMT‑associated molecular changes of LECs in traumatic cataract through transcriptional activation of THBS1, and regulated the expression of autophagy‑related markers in LECs, suggesting that KLF5/THBS1 axis might be a potential target for the treatment of traumatic cataract.

Cataract↗

PubMed2026

Multi-level aggregation analysis of microbiome composition and host gene expression reveals associations with systemic and local immunity.

The human gut microbiome plays a critical role in immune regulation, yet the molecular links between microbiome composition and host gene expression remain incompletely understood. We analyzed associations between host gene expression and microbiome composition in a cohort of 315 healthy individuals, integrating microarray-based gene expression data from three intestinal sites (ileum, transverse colon, and rectum) and six immune cell types with microbiome sequencing data. Using a hierarchical feature aggregation strategy combining principal component analysis, clustering, and covariate correction, we discovered significant associations primarily related to immunity. While microbial profiles were similar across the three intestinal sites, the transverse colon yielded the most "microbiome-host gene expression" associations. Among the immune cell types, CD8+ cells showed the highest number of associations. The first principal component of microbiome composition, reflecting a gradient from commensals (e.g., Ruminococcaceae and Christensenellaceae) to proinflammatory taxa ([Ruminococcus] gnavus and Lachnoclostridium), correlated with the expression of TNF-α-linked genes (HMOX1, CPI17, HSD3B2, and SLC5A1). Among individual genera, Catenibacterium abundance was associated with gene expression in both intestinal and immune cells, including negative associations with MRPS21 (related to mitochondrial function) in the transverse colon and with CD8+ gene programs related to T cell differentiation. These findings align with emerging evidence implicating mitochondrial dysfunction in intestinal inflammation. Our results identify multi-level associations between the gut microbiome and host gene expression, suggesting potential mechanisms by which microbiota shape local and systemic immunity and vice versa. The implicated genes and taxa represent candidates for experimental validation to improve understanding of host-microbiome homeostasis and its disruption in disease.IMPORTANCEThe gut microbiome and immune system are engaged in a complex interplay throughout human life. While most associative studies focus on case-control comparisons-typically examining patients with conditions such as inflammatory bowel disease or metabolic diseases-less is known about the molecular links between the microbiome and immune system in healthy individuals. In this study of a large cohort of healthy individuals, we addressed this gap by applying multiscale modeling to tackle the high dimensionality of host-microbiome data. We identified multi-level associations between microbiome composition and host gene expression in both intestinal tissues and immune cells. These findings offer a valuable reference for understanding baseline host-microbiome communication and highlight molecular candidates-such as TNF-α-related genes and mitochondrial pathways-for future experimental validation.

Humans↗

PubMed2025

FOSB is a key factor in the genetic link between inflammatory bowel disease and acute myocardial infarction: multiple bioinformatics analyses and validation.

BACKGROUND: Inflammatory Bowel Disease (IBD), which includes Crohn's disease and ulcerative colitis, is associated with an increased risk of Acute Myocardial Infarction (AMI). The genetic mechanisms underlying this link are not well understood. METHODS: We downloaded IBD and AMI-related microarray datasets from the NCBI Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified and analyzed using enrichment analysis and Weighted Gene Co-expression Network Analysis (WGCNA). Machine learning techniques, including LASSO, random forest, and Boruta, were employed to screen for hub genes. These genes were validated through qRT-PCR and Western blotting. Single-cell sequencing was used to confirm findings. Additionally, potential therapeutic targets were identified using the Connectivity Map (CMap) database. RESULTS: Five key hub genes-THBD, FOSB, ADGPR3, IL1R2, and PLAUR-were identified as significantly involved in both IBD and AMI pathogenesis. A diagnostic model for AMI constructed using these hub genes demonstrated high predictive accuracy. Single-cell sequencing analysis and several potential drugs targeting these hub genes were identified, offering new therapeutic avenues. CONCLUSION: This study highlights the crucial role of FOSB and other hub genes in the comorbidity of IBD and AMI. The findings provide novel insights for early diagnosis and potential therapeutic strategies, emphasizing the importance of further investigation into these genetic links.

Humans↗

PubMed2025

Transcriptomic profile induced by calcitriol in CaSki human cervical cancer cell line.

The vitamin D endocrine system, primarily mediated by its main metabolite calcitriol and the vitamin D receptor (VDR), plays a critical role in numerous human physiological processes, ranging from calcium metabolism to the prevention of various tumors, including cervical cancer. In this study, we comprehensively investigated the genomic regulatory effects of calcitriol in a cervical cancer model. We examined the transcriptional changes induced by calcitriol in CaSki cells, a cervical cell line harboring multiple copies of HPV16, the primary causal agent of cervical cancer. Our microarray findings, revealed that calcitriol regulated over 1000 protein-coding genes, exhibiting a predominantly repressive effect on the CaSki cell transcriptome by suppressing twice as many genes as it induced. Calcitriol decreased EPHA2 and RARA expression while inducing KLK6 and CYP4F3 expression in CaSki cells, as validated by qPCR and Western blot. Functional analysis demonstrated that calcitriol effectively inhibited key processes involved in cancer progression, including cell proliferation and migration. This was further supported by the significant downregulation of MMP7 and MMP13 mRNA levels. Our microarray results also showed that, in addition to its effects on protein-coding genes, calcitriol significantly regulates non-coding RNAs, altering the expression of approximately 400 non-coding RNAs, including 111 microRNA precursors and 29 mature microRNAs, of which 17 were upregulated and 12 downregulated. Notably, among these calcitriol-regulated microRNAs are some involved in cervical cancer biology, such as miR-6129, miR-382, miR-655, miR-211, miR-590, miR-130a, miR-301a, and miR-1252. Collectively, these findings suggest that calcitriol exhibits a significant antitumor effect in this advanced cervical cancer model by blocking critical processes for tumor progression, underscoring the importance of maintaining adequate vitamin D nutritional status.

Humans↗

PubMed2026

MarkerMatch: a proximity-based probe-matching algorithm for joint analysis of copy-number variants from different genotyping arrays.

MOTIVATION: Copy-number variants (CNVs) are a form of genetic structural variation with increasing importance in complex human disorders. Both DNA sequencing and microarray data can be used to detect CNVs, which can be used in genetic association tests. Unlike genotypes, CNV detection in microarrays requires the use of observed intensity signals at each probe, which limits the imputability for analyses that span multiple array types. Thus far, a consensus set of probes (those present on all arrays) has been used to circumvent the problem of differing array-specific sensitivities. This has led to excessive reduction in overall sensitivity since arrays can have an undesirably low probe overlap. To overcome this limitation, we developed MarkerMatch, a proximity-based algorithm that matches probes across different genotyping microarrays to maximize the number of probes considered in the CNV calling algorithm, thereby increasing the resolution and sensitivity while preserving precision. RESULTS: By analyzing CNV calls from 4906 individuals genotyped across three different arrays, we show that the MarkerMatch approach improves sensitivity by increasing the density of probes available for CNV calling while maintaining precision or improving it relative to the current practice (e.g. use of consensus probes only). We further demonstrate that MarkerMatch matches the CNV detection from current practice in terms of F1 score and PPV for larger CNVs. We also optimize MarkerMatch parameters, DMAX and Method, and find an optimal DMAX setting at 10 kb, with no clear optimal candidate based on Method, indicating that parameters for this metric should be determined on a use case basis. AVAILABILITY: The R package for MarkerMatch is available at: https://github.com/FranjoIM/MarkerMatch. The code used for analysis and implementation is available at: https://doi.org/10.5281/zenodo.18460979. The live notebook is available at https://fivankovic.notion.site/2026-markermatch.

DNA Copy Number Variations↗

PubMed2014

Molecular heterochrony and the evolution of sociality in bumblebees (Bombus terrestris).

Sibling care is a hallmark of social insects, but its evolution remains challenging to explain at the molecular level. The hypothesis that sibling care evolved from ancestral maternal care in primitively eusocial insects has been elaborated to involve heterochronic changes in gene expression. This elaboration leads to the prediction that workers in these species will show patterns of gene expression more similar to foundress queens, who express maternal care behaviour, than to established queens engaged solely in reproductive behaviour. We tested this idea in bumblebees (Bombus terrestris) using a microarray platform with approximately 4500 genes. Unlike the wasp Polistes metricus, in which support for the above prediction has been obtained, we found that patterns of brain gene expression in foundress and queen bumblebees were more similar to each other than to workers. Comparisons of differentially expressed genes derived from this study and gene lists from microarray studies in Polistes and the honeybee Apis mellifera yielded a shared set of genes involved in the regulation of related social behaviours across independent eusocial lineages. Together, these results suggest that multiple independent evolutions of eusociality in the insects might have involved different evolutionary routes, but nevertheless involved some similarities at the molecular level.

Analysis of Variance↗

PubMed2026

Carrot Juice Intake Modulates Oncogenic and Inflammatory Pathways in Advanced Colorectal Adenomas: A Pilot Feasibility Study.

Carrots are a rich dietary source of carotenoids and polyacetylenes, bioactive compounds with demonstrated anti-inflammatory and anticancer properties in experimental models. Epidemiological evidence suggests that carrot consumption is associated with a reduced risk of colorectal cancer; however, clinical data linking carrot intake to molecular changes in premalignant colorectal tissue remain limited. In this pilot intervention study, 20 patients with advanced colorectal adenomas were enrolled. Fifteen participants consumed carrot juice daily for 21 days, while five served as untreated controls. Paired adenoma biopsies were collected before and after the intervention and were analyzed using gene expression microarrays to assess transcriptional responses. Carrot juice intake was well tolerated, with adherence exceeding 95% and no reported adverse events. Transcriptomic analysis revealed modulation of key pathways implicated in colorectal carcinogenesis, including downregulation of the WNT, PI3K-AKT, and MAPK signaling pathways, as well as cyclooxygenase-2-related inflammatory pathways and cytokine signaling. These changes were consistent with reduced oncogenic signaling and attenuation of inflammatory activity within adenoma tissue. In summary, short-term carrot juice consumption was associated with coordinated suppression of molecular pathways involved in colorectal adenoma progression. These findings provide preliminary clinical evidence that a whole-food dietary intervention may influence early carcinogenic processes and support the need for larger controlled studies evaluating clinical outcomes.

Journal Article↗

PubMed2025

Effect of Chang'an decoction on ulcerative colitis by regulating T helper 17 cells and regulatory T cellsRab27 in the p53/high mobility group box 1 pathway.

OBJECTIVE: To explore the effect of Chang'an decoction (, CAD) of ameliorating the immune imbalances in ulcerative colitis (UC) by regulating Rab27 in the P53/high mobility group box 1 pathway. METHODS: The functions and important signaling pathways of the Rab27- and UC-related genes were analyzed viathe use of microarray data from the gene expression omnibus database, gene ontology database, Kyoto encyclopedia of genes and genomes database and gene set enrichment analysis. Dextran sulfate sodium salt-induced colitis mouse model was used to verify the bioinformatics results. Colon length, body weight, and disease activity index were measured. Hematoxylin and eosin staining was applied to validate the histopathology. Tight junction proteins were detected by immunohistochemistry. The proportions of T helper 17 cells (Th17) and regulatory T cells (Treg) in mesenteric lymph nodes were measured viaflow cytometry. Proinflammatory cytokines like interleukin (IL) 17 (IL-17), IL-21 and IL-22 and anti-inflammatory cytokines like transforming growth factor β and IL-10 in the serum and colon of mice were detected by enzyme-linked immunosorbent assay and quantitative real-time polymerase chain reaction, respectively. The expression levels of high mobility group box 1 (HMGB1), P53 and phospho- P53 (P-P53) in colonic tissues were detected by immunofluorescence and Western blotting. RESULTS: Bioinformatics analysis revealed that compared with normal tissues, the expression of Rab27 was significantly increased in UC tissues. Receiver operating characteristic curve showed that Rab27 has the potential to be used as a biomarker for the diagnosis of disease activity. Enrichment analysis showed that UC and Rab27 were mainly associated with small molecule transport, nutrient metabolism, transmembrane transport and the downstream pathway of P53. According to animal experiments, the expression of Rab27 was increased in UC tissues, which aggravated the colonic pathological damage, activated the expression of HMGB1, and also leaded to the imbalance of Th17 and Treg cells. After CAD intervention, Rab27 overexpression, weight loss, colon shortening, and pathological damage were substantial reduced, the expression of tight junction proteins, zona occludens 1 and Occludin were increased. The effect of CAD at high-dose was more obvious. In addition, CAD upgraded the number of Treg cells and the production of TGF-β and IL-10, while decreasing the number of Th17 cells and the expression of inflammatory cytokines (IL-17, IL-21, and IL-22). Moreover, colon inflammation was alleviated by CAD, as indicated by the regulation of HMGB1 and P-P53 expression. CONCLUSION: The expression of Rab27, HMGB1 and P-P53 could be decreased by CAD, and the balance of Th17 and Treg cells as well as their related cytokines could be regulated by CAD.

Animals↗

PubMed2025

MarkerMatch: A Proximity-Based Probe-Matching Algorithm for Joint Analysis of Copy-Number Variants from Different Genotyping Arrays.

MOTIVATION: Copy-number variants (CNVs) are a form of genetic structural variation with increasing importance in complex human disorders. Both DNA sequencing and microarray data can be used to call CNVs, which can be used in association tests, such as association between CNV number and disease status. Unlike genotypes, CNV detection in microarrays requires the use of observed intensity signals at each probe, which limits the imputability for analyses that span multiple array types. Thus far, a consensus set of probes (the intersection encompassing the probes that occur in common on all arrays) has been used to circumvent the problem of differing array-specific sensitivities. This has, however, led to excessive reduction in overall sensitivity of CNV calls as arrays can have an undesirably low overlap of probe sets. To overcome this limitation, we developed MarkerMatch, a proximity-based algorithm that matches probes across different genotyping microarrays to maximize the number of probes considered in the CNV calling algorithm, thereby increasing the resolution and sensitivity while preserving precision. RESULTS: By analyzing CNV calls from 4,906 individuals genotyped across three different arrays (Global Screening Array, Omni2.5 array, and Omni Express Exome array), we show that the MarkerMatch approach improves sensitivity by increasing the density of probes available for CNV calling while maintaining precision or improving it relative to the current practice (e.g., use of consensus probes only). We further demonstrate that MarkerMatch exceeds the output from current practice in terms of F1 score, Fowlkes-Mallows index, and Jaccard index. We also optimize MarkerMatch parameters, D MAX and Method, and find an optimal D MAX setting at 10kb, with no clear optimal candidate based on Method, indicating that parameters for this metric should be determined on a use case basis.

Journal Article↗

PubMed2025

BMDx2: A Tool for Integrating Toxicogenomics-Based Dose-Dependency Analysis and AOP-Based Mechanistic Insights.

Despite the advent of mechanistic toxicology using omics data to link molecular perturbations with systemic outcomes, regulatory toxicology still lacks the application of mechanism-anchored metrics from such data. This is partially because traditional gene-centric analysis often falls short of linking molecular changes to adverse outcomes. To address this gap, BMDx2, an open-source tool that transforms multi-dose toxicogenomics datasets into quantitative, mechanistic evidence for human chemical safety assessment is developed. BMDx2 couples benchmark-dose modeling with Adverse Outcome Pathway (AOP) enrichment to derive transcriptomic-based points of departure, enabling potency ranking, chemical prioritization, and mechanistically anchored explanations of the effect of chemical exposures. BMDx2 can process a broad range of data, including DNA microarray and RNA sequencing studies. Here, case studies are used to illustrate the versatility of BMDx2 in characterizing the mechanism of action of chemicals. An initial case study on carbon nanotubes exposure applies integrative analysis of transcriptomics and genome-wide DNA methylation data, uncovering cellular reprogramming processes underlying fibrosis. A second case study on bleomycin exposure demonstrate how transcriptomic data alone can be mapped to fibrosis-related AOPs in a standardized, regulatory appropriate manner. Together, these examples show how BMDx2 supports the regulatory application of toxicogenomics and accelerates mechanism-based chemical safety evaluation.

Toxicogenetics↗

PubMed2026

Proteomics in environmental pollution research: Advances, challenges, and future directions.

Environmental proteomics has emerged as a powerful approach for elucidating the molecular mechanisms underlying pollutant-induced biological effects. Although this field has developed rapidly, the systematic review of recent proteomics applications in environmental pollution research remains limited. This review explored the emerging roles of toxicoproteomics in biomarker discovery and mechanistic elucidation, as well as ecotoxicoproteomics in ecological risk assessment and bioremediation strategies. Here, we review the field, highlighting recent trends such as the integration of proteomics with genomics, transcriptomics, and metabolomics to provide a comprehensive view of biological responses to environmental stressors. We further discuss the growing application of artificial intelligence in improving proteomics data interpretation and accelerating biomarker discovery. In addition, recent technological advances in environmental proteomics are highlighted, including next-generation tissue microarray proteomics, nanoscale proteomics, single-cell proteomics, and spatial proteomics. Despite its potential, proteomics faces challenges, such as high operational costs, computational complexity in analysis, and technical limitations in low-abundance protein detection. We propose that the convergence of proteomics with artificial intelligence and multi-omics approaches offers promising solutions to these challenges, enhancing the practical application of proteomics in environmental monitoring and risk assessment.

Proteomics↗